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Inflammatory Bowel Disease (IBD) is a group of chronic intestinal diseases, among which Crohn’s disease (CD) and ulcerative colitis (UC) represent the two main types. The differential diagnosis of these two disorders is often a significant challenge, as there is a lack of specific and non-invasive biomarkers. In this study, we assessed the serum profile of proinflammatory mediators (E- and P-selectin, CCL2, IL-1α, IL-12p70, TNF-α) in patients with IBD to identify biomarkers helpful in the differential diagnosis of CD and UC. The conducted statistical analyses revealed a significant increase in E-selectin, P-selectin, IL-1α, and IL-12p70 levels in the serum of CD patients compared to UC. The performed ROC curve analysis identified moderate values of E-selectin (AUC 0.752), P-selectin (AUC 0.733), and IL-1α (AUC 0.731) in differentiating CD from UC, while IL-12p70 presented a satisfactory value (AUC 0.695). Simultaneous measurements of each biomarker with serum calprotectin improved the ability of E-selectin (AUC 0.752 vs. 0.829), P-selectin (AUC 0.733 vs. 0.75), IL-1α (AUC 0.731 vs. 0.778), and IL-12p70 (AUC 0.695 vs. 0.714) to differentiate CD from UC. Moreover, we identified a significant relationship between the concentration of CCL2 (r = 0.566, p < 0.005) and TNF-α (r = 0.431, p < 0.05) and the disease activity expressed as the Mayo score in the UC group. We also identified a significant relationship between the concentration of E-selectin (r = 0.372, p < 0.05), CCL-2 (r = 0.55, p < 0.05), IL-1α (r = 0.637, p < 0.005), and TNF-α in the group of patients with UC. Another significant correlation in the UC group was noted in the case of E-selectin and IL-12p70 (r = 0.542, p < 0.05), as well as between IL1-α and P-selectin (r = 0.514, p < 0.05). The results obtained in this study indicate the potential use of E-selectin, P-selectin, IL-1α, and IL-12p70 serum profiles in differentiating CD from UC. Regarding the significant relationship of CCL2 and TNF-α with the Mayo score, these two biomarkers might be useful in assessing and monitoring the disease activity during UC. Full article

A progressive decline in tree growth may be induced by global warming, affecting tree health and eventually resulting in death, particularly for trees growing in rocky mountainous regions where seasonal droughts have become more pronounced. However, tree growth dynamics in areas experiencing pronounced climate change have received little attention. In this study, a total of 100 (10 m × 10 m) grid plots were investigated in planted forests of Chinese cork oak (Quercus variabilis Blume), which were established in the 1960s and 1970s in a rocky mountainous area near Beijing, northern China. Furthermore, the radial growth of Q. variabilis (a total of 843 trees sampled from the dominant [D], co-dominant [CD], and suppressed [S] crown classes) was analyzed using retrospective dendrochronology and generalized additive models. The effects of meteorological changes between 1962 and 2020 on radial growth across the three crown classes were examined using correlation analysis. The results indicated that the growth of Q. variabilis initially increased and then decreased after 2010 at the regional level, and these trends varied according to crown class. The radial growth of the D trees responded more positively to an increase in temperature and drought severity index (<0 for dry and >0 for wet conditions) compared with that of the CD and S trees. The growth of the D and CD trees continuously increased under higher temperatures during the rainy seasons (June to September); however, the increases were higher for D than for CD trees. In contrast, the radial growth of S trees declined. We confirmed the historical effects of rising temperatures on tree growth and health, which are linked to water availability. Our data suggested that Q. variabilis trees will be considerably affected by intensified droughts. This study furthers our knowledge regarding the impact of climate change on tree and forest growth and provides management strategies for afforestation projects in rocky mountainous areas that are facing climate change. Full article

Prolonged drought exacerbated by climate change in the Mesilla Valley, one of the major agricultural areas of New Mexico, USA, is causing a shortage of surface water from the Rio Grande for irrigation. Farmers in the Valley are using groundwater for irrigation and complementing it with limited surface water from the river (Rio Grande). Managing irrigation water better is vital to sustaining agriculture in the Valley. Remote sensing (RS)-based crop evapotranspiration (ETa) models offer significant advantages over traditional methods. The ET maps generated by these RS models provide valuable information that can be used to manage irrigation water and crops in water-scarce areas. This study used METRIC and SSEBop RS models to map the ET of alfalfa on a private farm that is managed as commonly practiced in the Valley. The integrated ET values of the two models are compared to those of the ETa measured using the eddy covariance method. The comparison showed that 91.55% of the variability in SSEBop ETa estimates can be explained by the variability in the METRIC ETa estimates, and the variability in eddy covariance ETa can explain 93.07% of the variability in METRIC ETa and 86.01% in the SSEBop Eta estimates. Both METRIC and SSEBop reflected the ETa of alfalfa during full growth and harvesting periods. However, the absolute percent mean relative difference (MRD) of ET was higher for two out of three cuttings by SSEBop (>32%) compared to those for METRIC and eddy covariance. The spatiotemporal variabilities in crop ET estimates using METRIC and SSEBop showed a need to improve on-farm irrigation conveyance and on-the-field irrigation efficiency. Overall, RS models can provide spatiotemporal maps of ET that can be used for decision-making to manage irrigation water better and improve crop yield on a field, farm, and regional scale. Full article

The state of well-being and health of our body is regulated by the fine osmotic and biochemical balance established between the cells of the different tissues, organs, and systems. Specific districts of the human body are defined, kept in the correct state of functioning, and, therefore, protected from exogenous or endogenous insults of both mechanical, physical, and biological nature by the presence of different barrier systems. In addition to the placental barrier, which even acts as a linker between two different organisms, the mother and the fetus, all human body barriers, including the blood–brain barrier (BBB), blood–retinal barrier, blood–nerve barrier, blood–lymph barrier, and blood–cerebrospinal fluid barrier, operate to maintain the physiological homeostasis within tissues and organs. From a pharmaceutical point of view, the most challenging is undoubtedly the BBB, since its presence notably complicates the treatment of brain disorders. BBB action can impair the delivery of chemical drugs and biopharmaceuticals into the brain, reducing their therapeutic efficacy and/or increasing their unwanted bioaccumulation in the surrounding healthy tissues. Recent nanotechnological innovation provides advanced biomaterials and ad hoc customized engineering and functionalization methods able to assist in brain-targeted drug delivery. In this context, lipid nanocarriers, including both synthetic (liposomes, solid lipid nanoparticles, nanoemulsions, nanostructured lipid carriers, niosomes, proniosomes, and cubosomes) and cell-derived ones (extracellular vesicles and cell membrane-derived nanocarriers), are considered one of the most successful brain delivery systems due to their reasonable biocompatibility and ability to cross the BBB. This review aims to provide a complete and up-to-date point of view on the efficacy of the most varied lipid carriers, whether FDA-approved, involved in clinical trials, or used in in vitro or in vivo studies, for the treatment of inflammatory, cancerous, or infectious brain diseases. Full article

The InterCriteria decision-making approach, known as InterCriteria analysis (ICrA), was applied here to optimize the experimental protocol when the surface electromyography (EMG) signals of upper arm human muscles are recorded. Ten healthy subjects performed cycling movements in the sagittal plane with and without added weight for ten, six, two, and one second, respectively, for each active phase. The EMG signals from six muscles, namely m. deltoideus pars clavicularis and pars spinata, m. brachialis, m. anconeus, m. biceps brachii, and m. triceps brachii caput longum, were recorded. ICrA was used on the obtained data to find correlations between the sixteen different phases, eight for elbow flexion and eight for elbow extension. Based on the obtained results, we proposed an optimized experimental protocol (OEP) that omits slower and more difficult tasks while saving crucial data. The optimized protocol consists of seven, instead of ten, tasks and takes three minutes less than the time taken for the full experimental protocol (FEP). The lower number of movements in the OEP could prevent physical and psychical fatigue, discomfort, or even pain in the investigated subjects. In addition, the time to train subjects, as well as the time to process the surface EMG data, can be significantly reduced. Full article

Image–text multimodal deep semantic segmentation leverages the fusion and alignment of image and text information and provides more prior knowledge for segmentation tasks. It is worth exploring image–text multimodal semantic segmentation for remote sensing images. In this paper, we propose a bidirectional feature fusion and enhanced alignment-based multimodal semantic segmentation model (BEMSeg) for remote sensing images. Specifically, BEMSeg first extracts image and text features by image and text encoders, respectively, and then the features are provided for fusion and alignment to obtain complementary multimodal feature representation. Secondly, a bidirectional feature fusion module is proposed, which employs self-attention and cross-attention to adaptively fuse image and text features of different modalities, thus reducing the differences between multimodal features. For multimodal feature alignment, the similarity between the image pixel features and text features is computed to obtain a pixel–text score map. Thirdly, we propose a category-based pixel-level contrastive learning on the score map to reduce the differences among the same category’s pixels and increase the differences among the different categories’ pixels, thereby enhancing the alignment effect. Additionally, a positive and negative sample selection strategy based on different images is explored during contrastive learning. Averaging pixel values across different training images for each category to set positive and negative samples compares global pixel information while also limiting sample quantity and reducing computational costs. Finally, the fused image features and aligned pixel–text score map are concatenated and fed into the decoder to predict the segmentation results. Experimental results on the ISPRS Potsdam, Vaihingen, and LoveDA datasets demonstrate that BEMSeg is superior to comparison methods on the Potsdam and Vaihingen datasets, with improvements in mIoU ranging from 0.57% to 5.59% and 0.48% to 6.15%, and compared with Transformer-based methods, BEMSeg also performs competitively on LoveDA dataset with improvements in mIoU ranging from 0.37% to 7.14%. Full article

Alzheimer’s disease was described more than 100 years ago and despite the fact that several molecules are being tested for its treatment, which are in phase III trials, the disease continues to progress. The main problem is that these molecules function properly in healthy neurons, while neuronal pathology includes plasma membrane disruption, malfunction of various organelles, and hyperphosphorylation of Tau and amyloid plaques. The main objective of this article is the discussion of a neuronal restoration therapy, where molecules designed for the treatment of Alzheimer’s disease would probably be more effective, and the quality of life of people would be better. Full article

With the widespread application of tagging materials, existing chemical tagging materials exhibit limitations in stability and detection under field conditions. This study introduces a novel magnetic detection scheme. Hydrophilic material-modified Fe₃O₄ nanoparticles (COOH-PEG@Fe₃O₄ NPs) were synthesized using the co-precipitation technique. The content of Fe₃O₄ nanoparticles in the magnetic tagging liquid can reach up to 10 wt% and remain stable in an aqueous phase system for seven days. This research details the preparation process, the characterization methods (IR, ¹HNMR, EDX, XRD, SEM, TEM, VSM, DLS), and the performance effects of the materials in magnetic tagging. Experimental results indicate that COOH-PEG@Fe₃O₄ NPs exhibit high remanence intensity (Br = 1.75 emu/g) and considerable stability, making it possible to quickly detect tagged liquids in the field using portable flux meters and optical pump magnetometers. This study provides new insights into the design and application of magnetic tagging materials, making it particularly suitable for long-term tagging and convenient detection in field scenarios. Full article

The spread of natural fires is a complex issue, as its mathematical modeling needs to consider many parameters. Therefore, the results of such modeling always need to be validated by comparison with experimental measurements under real-world conditions. Remote sensing with the support of satellite or aerial sensors has long been used for this purpose. In this article, we focused on data collection with an unmanned aerial vehicle (UAV), which was used both for creating a digital surface model and for dynamic monitoring of the spread of controlled grassland fires in the visible spectrum. We subsequently tested the impact of various processing settings on the accuracy of the digital elevation model (DEM) and orthophotos, which are commonly used as a basis for analyzing fire spread. For the DEM generated from images taken during the final flight after the fire, deviations did not exceed 0.1 m compared to the reference model from LiDAR. Scale errors in the model with only approximal WGS84 exterior orientation parameters did not exceed a relative accuracy of 1:500, and possible deformations of the DEM up to 0.5 m in height had a minimal impact on determining the rate of fire spread, even with oblique images taken at an angle of 45°. The results of the experiments highlight the advantages of using low-cost SfM photogrammetry and provide an overview of potential issues encountered in measuring and performing photogrammetric processing of fire spread. Full article

The global surge in multi-drug resistant bacteria, including extended-spectrum β-lactamase (ESBL)-producing Escherichia coli has led to a growing need for new antibacterial compounds. Despite being promising, the potential of fish-derived antimicrobial peptides (AMPs) in combating ESBL-producing E. coli is largely unexplored. In this study, native African catfish antimicrobial peptides (NACAPs) were extracted from the skin mucus of farmed African catfish, Clarias gariepinus, using a combination of 10% acetic acid solvent hydrolysis, 5 kDa ultrafiltration, and C₁₈ hydrophobic interaction chromatography. Peptides were then sequenced using Orbitrap Fusion Lumos Tribrid Mass Spectrometry. The identified peptides were screened for potential antibacterial activity using Random Forest and AdaBoost machine learning algorithms. The most promising peptide was chemically synthesized and evaluated in vitro for safety on rabbit red blood cells and activity against ESBL-producing E. coli (ATCC 35218) utilizing spot-on-lawn and broth dilution methods. Eight peptides ranging from 13 to 22 amino acids with molecular weights between 968.42 and 2434.11 Da were identified. Peptide NACAP-II was non-hemolytic to rabbit erythrocytes (p > 0.05) with a zone of inhibition (ZOI) of 22.7 ± 0.9 mm and a minimum inhibitory concentration (MIC) of 91.3 ± 1.2 μg/mL. The peptide is thus a candidate antibacterial compound with enormous potential applications in the pharmaceutical industry. However, further studies are still required to establish an upscale production strategy and optimize its activity and safety in vivo. Full article

Human tumors progress in part by accumulating epigenetic alterations, which include gains and losses of DNA methylation in different parts of the cancer cell genome. Recent work has revealed a link between these two opposite alterations by showing that DNA hypomethylation in tumors can induce the expression of transcripts that overlap downstream gene promoters and thereby induce their hypermethylation. Preliminary in silico evidence prompted us to investigate if this mechanism applies to the locus harboring AGO1, a gene that plays a central role in miRNA biogenesis and RNA interference. Inspection of public RNA-Seq datasets and RT-qPCR experiments show that an alternative transcript starting 13.4 kb upstream of AGO1 (AGO1-V2) is expressed specifically in testicular germ cells, and becomes aberrantly activated in different types of tumors, particularly in tumors of the esophagus, stomach, and lung. This expression pattern classifies AGO1-V2 into the group of “Cancer-Germline” (CG) genes. Analysis of transcriptomic and methylomic datasets provided evidence that transcriptional activation of AGO1-V2 depends on DNA demethylation of its promoter region. Western blot experiments revealed that AGO1-V2 encodes a shortened isoform of AGO1, corresponding to a truncation of 75 aa in the N-terminal domain, and which we therefore referred to as “∆NAGO1”. Interestingly, significant correlations between hypomethylation/activation of AGO1-V2 and hypermethylation/repression of AGO1 were observed upon examination of tumor cell lines and tissue datasets. Overall, our study reveals the existence of a process of interdependent epigenetic alterations in the AGO1 locus, which promotes swapping between two AGO1 protein-coding mRNA isoforms in tumors. Full article

The potential of unconventional hydrocarbon resources has been unlocked since the hydraulic fracturing technique in combination with long horizontal wells was applied to develop this type of reservoir economically. The design and optimization of the fracturing treatment and the stimulated reservoir volume and the forecasting of production performance are crucial for the development and management of such resources. However, the production performance of tight gas reservoirs is a complicated nonlinear problem, described by many parameters loaded with uncertainty. The complexity of the problem influences and inspires the sophistication of the solution to be used. This paper proposed an artificial network model that allows for fast, extended, and accurate analyses of the production performance of multiple fractured unconventional tight gas wells. In the comprehensive approach developed, the reservoir rock parameters, the drainage area, and the hydraulic fracture parameters are treated as a variable input to the model. The analysis is no longer constrained by fixed “shoes box” geometry, and the values of the parameters defining the reservoir and stimulated volume are not limited to a few discrete values. The numerical experiment used to construct a database for model development was designed using a genetically optimized Latin hypercube sampling technique. A special approach was used in the preparation of “blind data”, which are crucial for truly reliable model verification. In the result, a developed tool offers an extended rock-fluid description, flexible model, and stimulated reservoir volume dimensioning and parameterization, as well as a high degree of applicability in sensitivity analysis and/or optimization. Full article

Cereals are an important source of nutrients, especially used in complementary feeding. The objective of this study is to review the nutritional composition of cereal-based foods for infants from 4 months and toddlers that are offered in Spain and Ecuador, countries selected because of the opportunity to work in them, and due to their socio-economic differences (industrialized and developing countries, respectively). The number of these products was 105 cereals in Spain and 22 in Ecuador. The products were classified as gluten-free cereals, five cereals, eight cereals, multigrain cereals, and cookies. A 25 g serving was used to determine the percentage in which the samples analyzed can cover the Reference Nutrient Intake (RNI) for micronutrients in infants from 7 months and toddlers according to the European Food Safety Authority (EFSA). Nutritional information per 100 g of dry product was collected according to medium, minimum, and maximum units, and nutrient density was calculated. The age range in which these products are recommended is different in both countries. The nutritional composition presents some differences; Spanish cereals show a lower content of sodium, added sugars, hydrolyzed cereals, and maltodextrin than Ecuadorian cereals. Commercialized cereals could contribute to satisfying the nutritional needs of infants and toddlers; however, they can also be a source of non-recommended components. Full article

The purpose of this study was to determine the impact of an antimicrobial peptide, BiF2_5K7K, on semen quality and bacterial contamination in boar semen doses used for artificial insemination. A key factor affecting semen quality and farm production is bacterial contamination in semen doses. Using antibiotics in a semen extender seems to be the best solution for minimizing bacterial growth during semen preservation. However, concern regarding antibiotic-resistant microorganisms has grown globally. As a result, antimicrobial peptides have emerged as interesting alternative antimicrobial agents to replace the current antibiotics used in semen extenders. BiF2_5K7K is an antimicrobial peptide that can inhibit Gram-negative and Gram-positive bacteria isolated from boar semen and sow vaginal discharge. In this study, ten fresh boar semen samples were collected and diluted with one of two types of semen extender: with (positive control) or without (negative control) an antibiotic (i.e., gentamicin). The semen extender without an antibiotic contained antimicrobial peptide BiF2_5K7K at different concentrations (15.625, 31.25, 62.5, and 125 µg/mL). The samples were stored at 18 °C until use. Semen quality parameters were assessed on days 0, 1, 3, and 5, and the total bacterial count was also evaluated at 0, 24, 36, 48, and 72 h after storage. A fertility test on a pig farm was also performed via sow insemination with a commercial extender plus BiF2_5K7K at a concentration of 31.25 µg/mL. No significant difference was found in terms of semen quality on days 0 or 1. On days 3 and 5, the total motility, progressive motility, and viability remained normal in the 15.625 and 31.25 µg/mL groups. However, the sperm parameters decreased starting on day 3 for the 125 µg/mL group and on day 5 for the 62.5 µg/mL group. For total bacterial count at 0, 24, 36, 48, and 72 h, the lowest bacterial count was found in the positive control group, and the highest bacterial count was found in the negative control group compared with the other groups. Comparing antimicrobial peptide groups from 0 to 48 h, the lowest bacterial count was found in the 125 µg/mL group, and the highest bacterial count was found in the 15.625 µg/mL group. For the fertility test, artificial insemination was conducted by using a commercial extender plus BiF2_5K7K at a concentration of 31.25 µg/mL. The results showed a superior pregnancy rate, farrowing rate, and total number of piglets born compared with artificial insemination conducted using a commercial extender plus antibiotic. In conclusion, BiF2_5K7K can inhibit bacterial growth in extended boar semen for 24 h, and thereafter, the bacterial count slightly increases. However, the increase in the number of bacterial counts from days 0 to 3 had no negative effect on sperm quality in the positive control, 15.625, or 31.25 µg/mL groups. This indicates that BiF2_5K7K might be an antimicrobial peptide candidate with potential for use as an alternative antimicrobial agent to replace the conventional antibiotic used in boar semen extenders. Full article

In European mountains most beech forest areas have been managed for timber production. This practice has reduced the availability of biomass for the whole forest-dwelling species assemblage and of deadwood for the saproxylic community. Despite most of Italy’s beech stands having a long history of management, its effects on forest species remain poorly understood. To address this gap, we studied beetle abundance and diversity in five beech-dominated forests with increasing management intensity in central Italy’s Apennines (Tuscany). We assessed if forests with similar management intensity exhibited comparable patterns in beetle diversity, abundance, and commonness versus rarity. Three forests were managed with even-aged shelterwood; one was managed with continuous cover forestry; and one was old-growth. We found 25 beetle families and 195 species across all sites with similar total abundance and richness. However, the representation of the most abundant families varied among sampling sites (ANOVA test: always significant for the total abundance of the most abundant families: F ≥ 2.77, d.f. = 4, p ≤ 0.038). The old-growth forest harbored more threatened species than managed sites. Saproxylic assemblages were similar between the recently cut site and the old-growth forest, and between shelterwood and continuous cover sites. While the similarity gradient among the whole species assemblages reflected geographical proximity, the similarity gradient among saproxylic assemblages reflected the successional proximity among forest management systems. Our research underscores the effects of management on beetle diversity, offering insights for sustainable forestry. Full article